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Record W2608116002 · doi:10.1098/rspb.2017.0236

Adaptation to a latitudinal thermal gradient within a widespread copepod species: the contributions of genetic divergence and phenotypic plasticity

2017· article· en· W2608116002 on OpenAlexaboutno aff
Ricardo J. Pereira, Matthew Sasaki, Ronald S. Burton

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsEuropean Commission
KeywordsBiologyPhenotypic plasticityAdaptation (eye)EcologyLocal adaptationContext (archaeology)LatitudeEctothermMicroevolutionEvolutionary biologyPopulationGeography

Abstract

fetched live from OpenAlex

Understanding how populations adapt to heterogeneous thermal regimes is essential for comprehending how latitudinal gradients in species diversification are formed, and how taxa will respond to ongoing climate change. Adaptation can occur by innate genetic factors, by phenotypic plasticity, or by a combination of both mechanisms. Yet, the relative contribution of such mechanisms to large-scale latitudinal gradients of thermal tolerance across conspecific populations remains unclear. We examine thermal performance in 11 populations of the intertidal copepod Tigriopus californicus , ranging from Baja California Sur (Mexico) to British Columbia (Canada). Common garden experiments show that survivorship to acute heat-stress differs between populations (by up to 3.8°C in LD 50 values), reflecting a strong genetic thermal adaptation. Using a split-brood experiment with two rearing temperatures, we also show that developmental phenotypic plasticity is beneficial to thermal tolerance (by up to 1.3°C), and that this effect differs across populations. Although genetic divergence in heat tolerance strongly correlates with latitude and temperature, differences in the plastic response do not. In the context of climate warming, our results confirm the general prediction that low-latitude populations are most susceptible to local extinction because genetic adaptation has placed physiological limits closer to current environmental maxima, but our results also contradict the prediction that phenotypic plasticity is constrained at lower latitudes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.241
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations107
Published2017
Admission routes1
Has abstractyes

Explore more

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